Scale-free networks in metabolomics

Abstract

Metabolomics is an expanding discipline in biology. It is the process of portraying the phenotype of a cell, tissue or species organism using a comprehensive set of metabolites. Therefore, it is of interest to understand complex systems such as metabolomics using a scale-free topology. Genetic networks and the World Wide Web (WWW) are described as networks with complex topology. Several large networks have vertex connectivity that goes beyond a scale-free power-law distribution. It is observed that (a) networks expand constantly by the addition of recent vertices, and (b) recent vertices attach preferentially to sites that are already well connected. Scale-free networks are determined with precision using vital features such as a structure, a disease and a patient. This is pertinent to the understanding of complex systems such as metabolomics. Hence, we describe the relevance of scale-free networks in the understanding of metabolomics in this article. Background: Metabolomics is the powerful high throughput technology in light of the whole set of metabolites that provide potential information since it measures and quantifies the outcome of cellular metabolism [1]. A critical challenge for biology and medicine is to achieve a comprehensive understanding of the operation of complex cellular systems as a whole since extensive knowledge about the individual components of living cells is insufficient. The dynamic behavior of biological systems is regulated by complex network of interactions between individual components [2].